This data release contains the $-2\DeltalogL$ maps in 2D ($\sin^2(\theta_{23})$ and $\Delta m^2_32$) that corresponds to the data in arXiv:2405.02163 [hep-ex]. The test-statistic in the analysis is a log-likelihood as defined in Eq.2 in arXiv:2405.02163.

Apart from the README, there are 2 numpy files and 1 python script:

- "saved_no_delta_LLH_map.npy" contains the map assuming normal ordering, with 29 points of $\Delta m^2_32$ and 39 points of $\sin^2(\theta_{23})$. 

- "saved_io_delta_LLH_map.npy" contains the map assuming inverted ordering, with 31 points of $\Delta m^2_32$ and 39 points of $\sin^2(\theta_{23})$. 

-The .npy files contain the value of $\Delta m^2_32$ in eV^2 (labeled "deltam232"), the value of $\sin^2(\theta_{23})$ (labeled "sin2_theta23"), and the corresponding $-2\DeltalogL$ (labeled "deltallh"), where the $-2\DeltalogL$ calculated as the difference between the LLH values of the scanned points and the best-fit point in each ordering respectively. They also contain the values of the best-fit parameters assuming each ordering, labeled "bfp_sin2th23" and "bfp_dm232". Since the best-fit points in each ordering were not forced to be contained in the scanned grid, the minima of the maps are not necessary to be zero. 

-The difference of the minima of the $-2\DeltalogL$ values between the two orderings are not included in this release. 

-"script.py" is an example python script that shows how to read the numpy files. This script reads the data in the numpy files, saves it to text files, and prints out the best fit point in each ordering.

Additional notes:

-The $-2\DeltalogL$ maps are only done in 2D, $\sin^2(\theta_{23})$ and $\Delta m^2_32$. The details of the free nuisance parameters in the fit can be found in arXiv:2405.02163. This analysis is insensitive to $theta_{13}$ and $delta_{CP}$ so that we fix their values at 8.61 degree and 0 degree respectively. We also use the following values in the fit: $theta_{12}$=33.82 degree, $\Delta m^2_{21}$=7.39e-05 eV^2. 